The crystallographic data of minerals from the group of britholite
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Distribution of described minerals from the supergroup of apatite (discredited species are also included) among individual groups (a) and distribution of kind of XO4 tetrahedra (b), crystal system (c) and space group (d) among these species.
Other minerals from the supergroup of apatite include 65%, i.e. 28 described mineral species Fig. 1(a), which predominantly crystallize in hexagonal system (
Frequency of XO4 ions and point groups for individual groups from the supergroup of apatite.
Hedyphane (Ca2Pb3(AsO4)3Cl), calcium-lead chloroarsenate [1],[2],[3],[4] is a mineral that was originally described from Langban, Sweden. It also occurs at the Harstig Mine, Pajsberg, Sweden and was moderately abundant at the Franklin Mine, Franklin, Sussex County, New Jersey. The mineral occurs in the localities introduced in Fig. 3. The mineral was named in 1830 by German mineralogist Johann Friedrich August Breithaupt [5] and its Greek name is usually translated as “pleasant appearance or beautifully bright.”
\nKnown localities for the mineral hedyphane.
The structure (perspective view according to the
The neotype (refer to Also described as “white variety” of “green lead ore” [4], i.e. the mineral mimetite ( Crystal habit shows well-formed and easily recognized faces. On the contrary, crystal faces that are not well formed are termed as anhedral. The intermediate texture between euhedral and anhedral is called subhedral.
The unit cell parameters of hedyphane are
The average length of Ca-O(
The coordination polyhedron around the Pb site in hedyphane (projection on 001). The number within the circle denotes
Fluorphosphohedyphane (Ca2Pb3(PO4)3F, [1],[8]): occurs in the oxidation zone of a small Pb-Cu-Zn-Ag deposit in the Blue Bell claims, about 11 km west from Baker, San Bernardino County, California (Fig. 6). Fluorphosphohedyphane is a fluor-analogue of phosphohedyphane, forms subparallel intergrowths and irregular clusters of transparent, colorless, highly lustrous, hexagonal prisms with pyramidal terminations.
\nThe locality for the mineral phosphohedyphane.
Fluorphosphohedyphane is found in cracks and narrow veins in highly siliceous hornfels The name for this type of contact metamorphic rock was given by K. von Leonhardt. The name originates from the designation of the highest peaks in the Alps but it can be also derived from ancient mining term from Saxony (Germany) which was used to describe hard, compact metamorphic rock developed at the margin of an igneous body. These rocks possess outstanding toughness due to fine-grained nonaligned crystals of platy or prismatic habit. Hornfels are sometimes banded, but their texture can be also porphyroblastic, i.e. they occur as large crystals within fine ground groundmass of metamorphic rock [9]. The name of the mineral comes from the Greek words
The structure (perspective view along the In the clinographic projection the crystal is turned by angle
Fluorphosphohedyphane has the apatite structure with the ordering of Ca and Pb in two cation sites, as in hedyphane and phosphohedyphane. The Pb2+ cation exhibits a stereoactive 6 The electronic configuration for Pb is [Xe] 4f14 5d10 6s2 6p2. Cations with formal ns2 np6 electronic configuration usually display novel properties and it is widely believed that the so-called n
The mineral is brittle with subconchoidal fracture and no cleavage. Based on the empirical formula, the calculated density is 5.45 g·cm−3. Fluorphosphohedyphane is hexagonal with the space group P63/m and the cell parameters
Phosphohedyphane (Ca2Pb3(PO4)3Cl [1],[22]): the mineral from the Capitana mine, Copiapó, Atacama Province, Chile, discovered in 2004. Known localities for the mineral phosphohedyphane are introduced in Fig. 8. Phosphohedyphane is brittle with subconchoidal fracture and no cleavage. Phosphohedyphane is hexagonal with the space group P63/m and the cell parameters
Known localities for the mineral phosphohedyphane.
The structure (perspective view along the
The mineral is a phosphate analogue of hedyphane and possesses an apatite structure with the ordering of Ca and Pb in two nonequivalent large cation sites. The structure refinement indicates that the Ca(2) sites are completely occupied by Pb and the Ca(1) sites contain 92% Ca and 8% Pb. The tetrahedral site refines to 91% P and 9% As. The refinement indicates the 0,0,0 position to be fully occupied by Cl. The structure and the crystal habit of phoshohedyphane are shown in Fig. 9.
\nOther secondary minerals identified in the oxidized zone together with phosphohedyphane are: anglesite (PbSO4 [25]), arsentsumebite (Pb2Cu(AsO4)(SO4)(OH) [26],[27]), azurite (Cu3(CO3)2(OH)2 [28]), beaverite The minerals beaverite-(Cu) and beaverite-(Zn), i.e. PbZnFe3+2(SO4)2(OH)6 [29], were recognized. Beaverite is an old name for the mineral beaverite-(Cu). There is also an orthorhombic polymorph (PMCN) aragonite.
Morelandite (Ca2Ba3(AsO4)3Cl, (Ba, Ca, Pb)5(AsO4, PO4)3Cl [1],[35],[36]), is a mineral that was named in 1978 according to Moreland. It occurs as small irregular masses associated with hausmannite (Mn2+Mn3+2O4 [37]) and calcite in the Jakobsberg mine, near Nordmark, Sweden (Fig. 10). The structure of morelandite is shown in Fig. 11.
\nKnown locality of the mineral morelandite.
The structure of morelandite (perspective view according to the
The mineral is gray to light yellow with white streaks, greasy to vitreous luster, and shows poor cleavage on {001}. Morelandite is hexagonal with the space group P63/m and the cell parameters
Aiolosite (Na2(Na2Bi)(SO4)3Cl, ideally Na4Bi(SO4)3Cl [7]): hexagonal mineral with the space group P63/m and the cell parameters
The locality of the mineral aiolosite.
The structure of the mineral aiolosite is shown in Fig. 13.
\nThe structure of aiolosite shows two independent cationic sites M(1) and M(2). Due to close similarity in ionic radii of Na+ and Bi3+, Bi exclusively prefers the M(2) site instead of M(1), which can be ascribed mainly to the Coulombic effect, in view of the higher charge of Bi3+ compared to Na+, since the average M(2)-O distance (2.516 Å) is shorter than that of M(1)-O (2.617 Å). A similar effect also affects the distribution of Na+ and Ca2+ sites in cesanite (
The structure of aiolosite (perspective view according to the
Caracolite (Na2(Pb2Na)(SO4)3Cl, sodium lead hydroxylchlorosulfate [1],[42],[43],[44]), is a vitreous colorless or grayish mineral from Beatriz mine, Caracoles, Chile, which was reported by Websky in 1886. Known localities and the structure of the mineral caracolite are shown in Fig. 14. It occurs as crystalline incrustations with imperfect pseudohexagonal crystals up to 1 mm large. The crystals have the form of hexagonal pyramids with the base and the prism, but they are supposed to be pseudohexagonal. The mineral exhibits complex polysynthetic twinning with rather large extinction angles.
\nThe localities of the mineral aiolosite.
The structure of caracolite (perspective view according to the
Caracolite is monoclinic mineral with the space group P21/m and the cell parameters
Cesanite (Ca2Na3(SO4)3OH [45],[46],[47]) is a colorless, medium to coarse-grained, soft mineral which occurs both as a solid vein (1 cm thick) and as cavity-filling of an explosive breccia in core samples of the Cesano-I geothermal well (Cesano area, Latium, Italy). Cesanite was recognized as new mineral by Cavarreta et al [47]. The crystal structure determination confirms that cesanite has to be considered a member of the apatite-wilkeite-ellestadite series, where (PO4)3− is entirely substituted by (SO4)2−, the charge balance being made up by partial substitution of Na+ for Ca2+ and H2O for (OH−, Cl− , F−).
\nThe general formula of this series, proposed by Harada et al [48] and modified by Cavarreta et al [47], is as follows:
where
Cesanite is a hexagonal mineral with the space group \n
The structure of cesanite is shown in Fig. 16. Synthetic and natural cesanite show typical elements of the apatite structure, but the reduction of symmetry from the centrosymmetric space group P63/m to the noncentrosymmetric space group \n
The structure of cesanite (perspective view according to the
The minerals from the group of belovite are cation ordered. Strontium substitutes for Ca in the M(2) site, and Na + REE substitute for Ca in the M(1) site. This results in lowering of symmetry from P63/m (the space group of the apatite archetype structure) to P63 (fluorstrophite, fluorcaphite), \n
Belovite-(Ce) (NaCeSr3(PO4)3F [49],[50],[51]), is a mineral from alkaline pegmatite in differentiated alkalic massifs which was named in 1954 by L.S. Borodin and M.E. Kazakova according to Russian mineralogist and crystallographer N.V. Belov. The mineral is found in Russia, on Mts. Punkaruaiv, Lepkhe-Nelm, Sengischorr, Karnasurt, Kedykvyrpakhk and Alluaiv, Lovozero massif; and on Mts. Kukisvumchorr and Koashva, Khibiny massif, Kola Peninsula. The localities of belovite-(Ce) are shown in Fig. 17.
\nThe localities of the mineral belovite-(Ce).
The mineral belovite-(Ce) is usually associated with ussingite (Na2AlSi3O8(OH) [52]), natrolite (Na2(Si3Al2)O10·2H2O [53]), chkalovite (Na2BeSi2O6 [54]), epistolite (Na4TiNb2 (Si2O7)2O2(OH)2·4H2O [55]), tugtupite (Na4BeAlSi4O12Cl [56]), manganneptunite (Na2KLi(Mn2+,Fe2+)2Ti2[Si8O24] and manganoneptunite [57] (the mineral is isostructural with neptunite [58],[59]), murmanite (Na2Ti2(Si2O7)O2·2H2O [60]), gaidonnayite (Na2ZrSi3O9·2H2O [61]), nordite-(La) (Na3SrLaZnSi6O17), lamprophyllite (Na3(Sr,Na)Ti3(Si2O7)2O2(OH)2 [62]), fluorcaphite, lomonosovite, deloneite-(Ce), sitinakite (KNa2Ti4Si2O13(OH)·4H2O [63]), aegirine (NaFe3+Si2O6 [64]), sodalite (Na4Si3Al3O12Cl [65]), microcline Originally, the mineral was named as mikroklin [66],[67]: triclinic mineral, space group \n
The structure of belovite-(Ce) (perspective view according to the
Belovite-(Ce) is the cerium analogue of belovite-(La) ( Latin phrase (abbreviated as s.s.) used, which means “in exact sense.”
Belovite-(Ce) is a brittle mineral with a honey-yellow or greenish color that crystallizes in trigonal system with the unit cell parameters Cleavage that is parallel to the orientation {0001}, i.e. to the base of crystal.
Belovite-(La) (NaLaSr3(PO4)3F [1],[69]) was named according to N.V. Belov (
The structure (shown along the
The mineral belovite-(La) crystallizes as trigonal in the space group \n
The locality of belovite-(La).
Belovite-(La) can be found in natrolite veinlets Sheetlike body of minerals which crystallize within the rock.
Carlgieseckeite-(Nd) The holotype material is deposited in the Fersman Mineralogical Museum of Russian Academy of Sciences, Moscow [72].
The structure of the mineral (Fig. 21) is representative of the structure type of belovite
The structure of carlgieseckeite -(Nd) (perspective view according to the
Mineral carlgieseckeite-(Nd) is trigonal, from the space group \n
Deloneite ((Na0.5REE0.25Ca0.25)(Ca0.75REE0.25)Sr1.5(CaNa0.25REE0.25)(PO4)3F0.5(OH)0.5 [1],[76]): the name of the mineral was changed from deloneite-(Ce) to deloneite. The mineral was named by Khomyakov, Lisitin, Kulikova and Rastsvetaeva in 1996 according to Russian mathematical crystallographer Boris Nikolaevich Delone. The mineral usually occurs as anhedral to subhedral2 crystals in the matrix. The locality and the structure of the mineral are shown in Fig. 22 and Fig. 23, respectively.
\nThe locality of deloneite.
The structure of the mineral deloneite (perspective view according to the
Deloneite is a bright yellow mineral which crystallizes in trigonal systems with the unit cell crystallographic parameters
Fluorcaphite (SrCaCa3(PO4)3F [1],[77],[78]): the name of this mineral is an acronym for its elemental composition, i.e. fluorine, calcium and phosphorus. Fluorcaphite is a common accessory mineral in albitite, Granular rock essential consisting of the mineral albite. Coarse-grained intrusive rock crystallized slowly under conditions similar to granite, but is deficient of quartz.
Fluorcaphite forms euhedral prismatic crystals up to 0.3 mm in length. Most of the crystals are homogeneous, but a few contain resorbed core relatively depleted in Sr, Na and light rare-earth elements (LREE). This pattern of zoning arose from two overprinting episodes of metasomatism The term was introduced by Neumann [83]. Metasomatism is a metamorphic process by which the chemical composition of a rock or rock portion is altered in a pervasive manner and which involves the introduction and/or removal of chemical components as the results of the interaction of the rock with aqueous fluids (solutions). During the metasomatism, the rock remains in a solid state.
The structure (view along
Fluorcaphite is light or bright yellow hexagonal mineral which crystallizes in the space group P63 with the crystallographic parameters
Fluorstrophite (SrCaSr3(PO4)3F [1],[85],[86]) formerly “strontium-apatite” [87] and later changed to apatite-(SrOH) [1]. It possesses massive, coarse granular to compact morphology. The crystal forms include short to long hexagonal prisms, they can also be thick and tabular. Similar to fluorcaphite, the name of the mineral reflects its chemical composition (fluorine, strontium and phosphorus). The localities of the mineral fluorstrophite are shown in Fig. 25.
\nLocalities for the mineral fluorstrophite.
The structure and the crystal habit of the mineral fluorstrophite.
The structure and the crystal habit of the mineral fluorstrophite are shown in Fig. 26. It is a green, yellow-green or colorless mineral with vitreous-greasy luster that crystallizes in hexagonal system with the space group P63/m or P63. The crystallographic parameters of the unit cell are
The mineral kuannersuite-(Ce) (Na2Ce2Ba6(PO4)6FCl [88]) was found and named according to the locality (Kuannersuit plateau) in the Ilímaussaq alkaline complex, South Greenland (Fig. 27). It occurs associated with the minerals including aegirine, analcime, beryllite (Be3SiO4(OH)2·H2O [89]), chkalovite, galena, gmelinite There are three minerals: gmelinite-(Ca), gmelinite-(K), and gmelinite-(Na) with the composition of Ca2(Si8Al4)O24·11H2O [90],[91], K4(Si8Al4)O24·11H2O [93], and Na4(Si8Al4)O24·11H2O [91],[93], respectively. The member of the pyrochlore group ((Na,Ca)2Nb2O6(OH,F)). A new scheme of nomenclature for the pyrochlore supergroup, approved by the CNMNC–IMA, is based on the ions at the A, B, and Y sites. The subgroups should be changed to the groups: pyrochlore (1), microlite (2), roméite (3), betafite (4), and elsmoreite (5). The new names are composed of two prefixes and one root name (identical to the name of the group). The first prefix refers to the dominant anion (or cation) of the dominant valence [either H2O or □] at the Y site. The second prefix refers to the dominant cation of the dominant valence [either H2O or □] at the A site. The prefix “keno–” represents “vacancy.” Where the first and the second prefix are equal, only one prefix is applied [100].
The locality for the mineral kuannersuite-(Ce).
It occurs as light rose-colored hexagonal prismatic crystals, up to 1.5 mm long, with a white streak and a vitreous luster. It is a barium analogue of belovite-(Ce) (
The structure and the crystal habit of the mineral kuannersuite-(Ce).
Kuannersuite-(Ce) crystallizes in trigonal systems with the space group \n
Britholites are typically phosphorus-bearing silicates with apatite structure and general formula: (REE,Ca)5[(Si,P)O4]3 The series of metamorphic processes whereby chemical changes occur in minerals or rocks as the result of the introduction of material, often in hot aqueous solutions, from external sources.
The structure and the crystallographic data of some of the minerals from the group of britholite were introduced in Fig. 29 and The structure (the view according to axis Fig. 29
Mineral name | \nCrystallographic parameters | \nHardness (Mohs) | \n||||||
---|---|---|---|---|---|---|---|---|
SG | \nDensity* | \n|||||||
[Å] | \n\n | — | \n— | \n[Å3] | \n— | \n[g·cm−3] | \n||
Britholite-(Ce) | \n9.63 | \n7.03 | \n1:0.730 | \n2 | \n564.60 | \nP63/M | \n4.45/4.49 | \n5½ | \n
Britholite-(Y) | \n9.43 | \n6.81 | \n1:0.722 | \n524.45 | \n4.25/4.07 | \n5.0 | \n||
Fluorbritholite-(Ce) | \n9.52 | \n6.98 | \n1:0.734 | \n547.74 | \n4.66/4.67 | \n|||
Fluorbritholite-(Y) | \n9.44 | \n6.82 | \n1:0.722 | \n526.68 | \n—/4.61 | \n5½ | \n||
Fluorcalciobritholite | \n9.58 | \n6.99 | \n1:0.729 | \n555.17 | \n4.20/4.25 | \n5½ | \n||
Tritomite-(Ce) | \n9.35 | \n6.88 | \n1:0.736 | \n520.89 | \n4.20/5.02 | \n5.5 | \n||
Tritomite-(Y) | \n9.32 | \n6.84 | \n1:0.734 | \n\n | 514.54 | \n\n | 3.22/4.48 | \n3.5-6.5 | \n
The crystallographic data of minerals from the group of britholite
Measured/calculated
The britholite-(Ce) (Lessignite-(Ce), (Ce,Ca)5(SiO4)3OH) [104],[105],[106]) mineral (Fig. 30) was first recognized as the new mineral by G. Flink (1897) in the pegmatite form of the nepheline–syenite at Naujakasik, Ilímaussaq complex, Greenland. Known localities for the mineral britholite are shown in Fig. 31.
\nThe crystal (13 mm) of britholite-(Ce) from Ostkogen, Tvedalen, Norway.
The localities for the mineral britholite-(Ce).
The specimen was named and described by Chr. Winther [104] as opaque, brown crystals of the composition of 3[4SiO2,2(Ce,La,Di,Fe)2O3,3(Ca,Mg)O,H2O,NaF],2[P2O5,Ce2O3], which are apparently hexagonal prisms with pyramids, but it actually consists of biaxial orthorhombic individuals twined together as in aragonite. The Th-rich britholite-(Ce) was also known as fenghuangshite [107]. Britholite-(Ce) (first described as britholite) is the forefather of the britholite group [108]. The structure of monoclinic britholite-(Ce) is shown in Fig. 32 and the crystallographic data are listed in
The crystal structure (perspective view according to
The crystal structure of monoclinic dimorphs Fig. 33 of the mineral britholite-(Ce) (and also of britholite-(Y)described below) was solved in
Depiction of Ca(1)-O(3) triangles in apatite (a) and REE(1)-O(3) triangles in hexagonal (b) and monoclinic britholite (
The mineral britholite-(Y) ((Y,Ca)5(SiO4)3OH, abukumalite, [105], [109]) occurs similarly to britholite-(Ce) in granite, alkaline rocks, skarns and hydrothermal veins [107]. The structure of monoclinic (P21, refer the discussion to Fig. 33) britholite-(Y) and known localities are shown in Fig. 35 and Fig. 34, respectively.
\nThe structure (perspective view along the
The localities for the mineral britholite-(Y).
Britholite-(Y) is very brittle mineral with reddish brown or black color, pale brown streak and resinous luster that crystallizes as hexagonal in the space group P63/m with the unit cell parameters
The mineral fluorbritholite-(Ce) ((Ce,Ca)5(SiO4)3F) [1],[110]) is the fluorine-rich analogue of britholite-(Ce). The structure and known localities of the mineral fluorbritholite-(Ce) are shown in Fig. 36 and Fig. 37, respectively. The mineral has a yellow, reddish-brown color, or The structure (perspective view along the Fig. 36
The localities for the mineral fluorbritholite-(Ce).
Fluorbritholite-(Ce) is a very brittle mineral that crystallizes as hexagonal in the space group P63/m. The unit cell shows following crystallographic parameters:
The mineral fluorbritholite-(Y) ((Y,Ca)5(SiO4)3F) [108]) was named as the fluorine-dominant analogue of britholite-(Y), where the Levinson-type suffix modifier, -(Y), indicates the dominance of yttrium among rare-earth elements. It forms irregular grains, hexagonal to tabular crystals and short-prismatic to thick-tabular crystals. The known localities and structures of the mineral fluorbritholite-(Y) are shown in Fig. 38 and Fig. 39, respectively.
\nThe structure (perspective view along the
The localities for the mineral fluorbritholite-(Y).
The mineral fluorbritholite crystallizes in hexagonal systems of the space group P63/m with the crystallographic parameters of unit cell
The mineral fluorcalciobritholite ((Ca,REE)5(SiO4,PO4)3F; [1],[102]) was found at Mount Kukisvumchorr, Khibiny alkaline complex, Kola Peninsula, Russia and differs from fluorbritholite and fluorapatite in the content of calcium (Ca >
The structure (perspective view along the
The localities for the mineral fluorcalciobritholite.
The ideal chemical formula for fluorcalciobritholite may be written as (Ca3REE2) [(SiO4)2(PO4)]F. In the view of coupled heterovalent substitutions occurring at the M and T sites in the series apatite–calciobritholite–britholite, it is more practical in this case for nomenclature purposes to consider the total abundance of M cations as a single, composite site [1].
\nPale pinkish brown or brown mineral fluorcalciobritholite crystallizes as hexagonal in the space group P63/m with the crystallographic parameters
Tritomite-(Ce) (Ce5(SiO4,BO4)3(OH,O) [105],[111]) was first found by Weibye in 1849 at the island of Låven in Langesundsfjord as dark tetrahedral crystals in leucophanite ((Na,Ca)2BeSi2(O,OH,F)7 [112] or analcime. Chemically and structurally, it is very similar to melanocerite (melanocerite-(Ce), Since the mineral is equal to tritomite-(Ce), the name of melanocerite-(Ce) is discredited [1].
The crystal habit of the mineral tritomite-(Ce) and tritomite-(Y).
The mineral was named from the Greek
Tritomite-(Ce) crystallizes as hexagonal mineral in the space group P63/m with crystallographic parameters
Known localities for the mineral tritomite-(Ce).
The mineral tritomite-(Y) ((Y5(SiO4,BO4)3(OH,O,F), [Y3+(Cr, Pr, Th)4+Ca](Si2B)O12O [111],[113],[115]) was first described by Frondel. It is also known as the hexagonal mineral spencite (named after Canadian geologist H.S. Spence) [116]. The mineral tritomite-(Y) is formed in the nepheline syenite pegmatites of the area, which carries rare earths predominantly from the yttrium group. Known localities of mineral tritomite-(Y) are introduced in Fig. 44.
\nKnown localities for the mineral tritomite-(Y).
When heated in air to temperatures ranging from 600°C to 1000°C, tritomite-(Y) recrystallizes to the structure of apatite and amorphous phase, presumably to a calcium borosilicate glass [60]. The pyramidal crystals of the mineral tritomite-(Y) are similar to tritomite-(Ce) ones, which are shown in Fig. 42.
\nTritomite-(Y) crystallizes as hexagonal in the space group P63/m with unit cell parameters
Ellestadites
The structural formula of ellestadite and (with slight modification) of wilkeite can be expressed as follows [117]:
This formula indicates that two-fifths of the Ca2+ ions are located on threefold axes and can be replaced by carbon. Three-fifths of the Ca2+ ions are tied to F−, Cl− and O− anions or OH− groups and cannot be replaced by carbon. All Ca2+ ions are tied to O-ions, which are arranged in tetrahedral coordination with S-, Si-, P- or C-ions at the centers.
\nThe mineral fluorellestadite (formerly called ellestadite-(F) [85],[118],[119] Ca5(SiO4)1.5 (SO4)1.5F [1],[120]) is a rare mineral found in nature in skarns or metamorphosed limestones Limestone is a name used for sedimentary rock composed mainly of calcium carbonate, usually in the form of calcite (trigonal CaCO3) or aragonite (orthorhombic CaCO3), but there could also be considerable amounts of magnesium carbonate (MgCO3, trigonal mineral magnesite) or dolomite (trigonal CaMg(CO3)2) [121].
Known localities for the mineral fluorellestadite.
Fluorellestadite is colorless, blue or pale bluish green hexagonal mineral belonging to the space group P63/m. The unit cell parameters are
The mineral is also known from burned coal dumps, where its formation is possible in the presence of carbonaceous and carbonate rocks such as the rests of pyrometamorphism The term pyrometamorphism, which is derived from the Greek word
The structure of the mineral fluorellestadite (perspective view along the
Hydroxylellestadite (formerly called ellestadite-(OH) [85], Ca5(SiO4)1.5(SO4)1.5(OH) [1],[117], [122],[123]) was first reported at cornet Hill by Pascal et al [124] and Marincea et al [125]. Natural hydroxylellestadite Synthetic analogs are known as “technical products,” such as burnt industrial waste and cement [122].
Known localities for the mineral hydroxylellestadite.
Hydroxylellestadite is associated with berlinite The mineral was named after Swedish pharmacologist N.J. Berlin. The mineral is Al-P analogue of quartz.
Hydroxylellestadite is a pink or purple-gray hexagonal mineral, which belongs to the space group P63/m. The unit cell parameters are
The structure (perspective view along the
The mineral chlorellestadite The IMA status of the mineral was discredited in 2010.
The mineral occurs as a compact mass. The mineral chlorellestadite is associated with diopside, wollastonite, vesuvianite (Ca10Mg2Al4(SiO4)5 (Si2O7)2(OH)4 [129]), monticellite (CaMgSiO4 [130]) and calcite.
\nThe structure of the mineral chlorellestadite (perspective view along the
Chlorellestadite is a hexagonal mineral that crystallizes in the space group P63/m with crystallographic parameters
Mattheddleite [131],[132],[133],[134] is a mineral with the composition Pb10(SiO4)3(SO4)3Cl2 (Livingstone et al [131]) or Pb5(Si1.5S1.5)O12(Cl0.57OH0.43) (Stelle et al [134]) which is a lead member of apatite supergroup where phosphorus is totally replaced by sulfur and silicon: Si4+ + S6+ ↔ 2P5+. Mattheddleite was first recognized in typical Pb mineral region at Leadhills, Scotland and named after Scottish mineralogist Matthew Forster Heddle (1828–1897). The
Mattheddleite is a colorless or white hexagonal mineral belonging to the space group P63/m. The unit cell parameters are
Known localities for the mineral mattheddleite.
The structure and the crystal habit of the mineral mattheddleite (perspective view along the
The mineral pieczkaite (Mn52+(PO4)3Cl [135],[136]) was found in the Southeastern shoreline of a small, unnamed island in Cross Lake, Manitoba, Canada (54°41′N, 97°49′W; Fig. 52) and classified as the member of the supergroup of apatite. It is isostructural with calcium fluorapatite (
Locality for the mineral pieczkaite.
The structure of the mineral pieczkaite (perspective view along the
It is a hexagonal mineral that crystallizes in the space group P63/m with the crystallographic parameters of unit cell
The coordination polyhedron around Mn(1) has the point-group symmetry 3 and is a trigonal prism in which the two triangles of oxygen atoms are slightly rotated relative to each other. The coordination polyhedron around Mn(2) is a severely distorted octahedron. The phosphate group is more distorted than in any of the other apatites. The chlorine atom is located in the center of an equilateral triangle formed by three Mn(2) atoms [136].
\nAs mentioned previously (
The carbonate-rich apatites are:
\n
This complex carbonate-substituted apatite is found only in marine environments, and, to a much smaller extent, in weathered deposits, for instance above carbonatites [138]. The mineral was named according to its occurrence at Wheal Franco, Whitchurch, Tavistock District, Devon, England. The structure and the crystal shape of carbonate-hydroxylapatite (a) and fluorapatite (b).Fig. 54
\n
\n
Radiating (previously incorrectly termed as staffelite)
Optically amorphous
The mineral is usually gray or brown due to the content of organic, humic or ferruginous impurities. Sometimes, it is white or black colored. Pure kurskite has a specific gravity of 3 g·cm−3.
\n
According to the accommodation of carbonate ion in the apatite structure, three basic types of apatites (Fig. 55) can be recognized [144]:
\n
\n
\n
Part of the
Individual types of carbonate apatite and their importance for bone and dental enamel are described in
Carbonate apatites have distinctive
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\n
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\n
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Historically, females have been omitted from addictions research. One reason for this omission is that ovarian hormones fluctuate rhythmically across females’ menstrual cycles and may impact their addictive behavior. As a result of this sex bias, theory and evidence pertaining to the nature, development, and maintenance of addiction are based primarily on research with male samples [1]. Given that females have been underrepresented in addictions research, many treatment and preventative intervention methods developed to date may not be suitable for females with addictions. This general failure to develop sex-specific treatment and prevention options is particularly problematic given the high occurrence of addictive behaviors in females. For example, the National Council on Alcoholism and Drug Dependence [2] has reported that 4.5 million American females abuse/are dependent on alcohol, 3.5 million misuse prescription drugs, and 3.1 million regularly use illicit drugs. Of further concern, the Substance Abuse and Mental Health Services Administration [3] has reported that 15.8 million American females, 18 years and older, have used illicit drugs within the past year. These statistics exemplify just how common addictive behaviors are in the female population.
\nOf further concern, the prevalence of addictive behaviors in females is increasing and closely approaching that of men. For example, increases in females’ alcohol consumption and alcohol use disorders are evident, with prevalence rates converging upon those reported for males [4]. The documented convergence between female and male alcohol consumption and alcohol use disorders may be explained by a societal shift toward an increased acceptance for females to engage in potentially addictive behaviors, such as alcohol consumption and tobacco use [5]. Thus, investigating sex-specific factors influencing addictive behaviors is critical for the development of effective treatment and prevention options for females with addictions.
\nAs a result of the current underrepresentation of females in addiction research and our substandard knowledge of sex-specific factors influencing addiction, many funding agencies (e.g., Canadian Institute of Health Research) have introduced a requirement that researchers consider sex when developing research questions and designs. With this sex-sensitive research focus, numerous researchers have begun exploring the potential influence of the menstrual cycle, a female-specific factor, on fluctuations in addictive behaviors (e.g., cigarettes smoked, gambling intensity) and mood (e.g., negative and positive affect).
\nTo effectively examine fluctuations in addictive behavior across the menstrual cycle, researchers have begun employing daily diaries—a prospective methodology where participants are asked to complete surveys at various time points throughout the day. Using daily diary surveys provides researchers with the advantage of obtaining intensive longitudinal data. However, variation in female menstrual cycle length has made it particularly difficult to conduct such daily diary menstrual cycle research due to the lack of established menstrual cycle standardization methodologies. Since researchers currently do not have a method to standardize variable menstrual cycle lengths, they are left with the sole option of breaking the menstrual cycle down into phases which vary not only in length across studies but also by the total number of menstrual cycle phases, which can be problematic.
\nCurrently, two predominant problems in menstrual cycle research are evident. First is the lack of comparability across studies with respect to the data which goes into each menstrual cycle phase. Although the division of data into menstrual cycle phases itself is not necessarily problematic, issues appear when inconsistencies arise within phase designation methods across studies. Researchers commonly divide the menstrual cycle into a different number of menstrual cycle phases, with each phase consisting of various days, which further confounds the picture. Inconsistencies in menstrual cycle phase designations were demonstrated in a literature review where studies reporting addictive behaviors across the menstrual cycle were examined. In our literature review, two studies, both examining sexual behavior across menstrual cycle phase, divided the menstrual cycle into two and seven menstrual cycle phases, respectively [6, 7]. Two additional studies, examining cigarette use/nicotine intake across the menstrual cycle, designated the premenstrual phase as 3 and 5 days prior to menstruation, respectively [8, 9]. With these evident discrepancies in menstrual cycle phase designation between studies, our ability to effectively compare research findings is substantially limited. To effectively compare research findings in the menstrual cycle field, the development of standardization methods is warranted. Given these problems, we propose a method to standardize menstrual cycle phase given variable menstrual cycle lengths across different female participants. Throughout this book chapter we will refer to this form of standardization as ‘phasic standardization’ which can be analyzed using statistical methods such as repeated-measures analyses of variance (ANOVAs), for example.
\nEven though phasic standardization eliminates one problem, another problem arises. When data is collapsed across days within phases, a daily average per phase is produced. However, collapsing data across menstrual cycle phase to produce a phasic average still results in a loss of potentially important information. Instead, data can be examined continuously across menstrual cycle days using another form of standardization to eliminate the problem of collapsing data across days within each menstrual cycle phase. As a solution to this second problem, we propose a method to standardize menstrual cycle day given variable menstrual cycle lengths across females. Throughout, we refer to this as ‘continuous standardization’1, which can be analyzed using data analytic techniques like time varying effects models (TVEMs).
\nThe current chapter aims to eliminate the standardization problem in menstrual cycle research by providing a method for researchers to standardize intensive longitudinal data collected using daily diary methodology across the female menstrual cycle. We will explain how researchers can standardize such intensive longitudinal data across the menstrual cycle using one of two methods (i.e., phasic or continuous standardization). We also provide two clinically-relevant hypothetical examples of the proposed standardization methods. We will also explore the statistical methods which can be used to analyze such standardized menstrual cycle data, including repeated measures ANOVAs and TVEMs. This book chapter may be of practical use to researchers working in the menstrual cycle field as it provides standardized methodology for examining fluctuations in dependent variables, such as substance use levels and mood, across the menstrual cycle. The purpose of this chapter is to provide standardization methods to examine menstrual cycle data as means to enhance our understanding of the menstrual cycle as a female-specific factor in the field of addiction and mental health.
\nOn average, a female’s menstrual cycle lasts between 23 and 35 days (average length = 28 days) [10], indicating a large range of individual variability in menstrual cycle length. Based on ovarian hormone fluctuations, the menstrual cycle has been divided into two overarching phases: the follicular (from menstrual bleeding until ovulation) and luteal phases (from ovulation until the day prior to menstrual bleeding) [11]. Furthermore, rhythmic fluctuations in progesterone, estrogen, follicle-stimulating hormone, and luteinizing hormone concentrations, allow for further subdivision of the menstrual cycle, resulting in the following five more specific phases: menstrual, follicular, ovulatory, luteal, and premenstrual [11, 12, 13, 14] (see Figure 1).
\nA depiction of the menstrual cycle divided into five specific phases.
Variability in female menstrual cycle length has been attributed to differing luteal phase lengths [15]. Although the literature is mixed in the sense that some literature points toward the follicular phase as the phase that contributes the most to menstrual cycle variability [16], the bulk of the literature suggests that the luteal phase is the main contributor to variance in menstrual cycle length [15]. That menstrual cycle length variability occurs specifically at the luteal phase is supported by two facts. Firstly, although the timing of the ovulatory phase may differ on an individual basis, research shows the ovulatory phase typically occurs between days 13–16 of the menstrual cycle [11] suggesting there is little variability prior to the ovulatory phase. The second is that the premenstrual phase has been defined as occurring 5 days prior to menstrual bleeding [17]. Thus, it is the luteal phase, which precedes the menstrual phase, that is subject to variable lengths. Based on the fact that variability in a female’s menstrual cycle occurs during the luteal phase, we have developed two methods to standardize menstrual cycle data, consisting of phasic and continuous standardization, respectively (see Sections 2 and 3 for methodological procedures and clinically-relevant hypothetical examples of the two standardization methods). It is cautioned that the two standardization methods described herein solely be implemented for menstrual cycle lengths between 23 and 35 days. Females with menstrual cycle lengths outside of the average 23–35 days should not be included in the menstrual cycle standardization methods discussed in this chapter. The accuracy of standardizing data from females with menstrual cycle lengths outside of the average 23- to 35-day range is questionable. Abnormally short/long menstrual cycles have an unduly influential role in ovarian hormone fluctuations. Thus, such individuals are typically categorized as not normally-cycling and are not included in studies of the normal female menstrual cycle [10].
\nIf a researcher is interested in variations in specific behaviors (e.g., substance use or other addictive behavior) occurring during certain phases of the menstrual cycle, we have developed a standardized method to examine phase-related changes in behavior. We refer to this standardization method as phasic standardization. In this method, data collected via daily diary across an entire menstrual cycle is standardized as a means for examining addictive behaviors by phase rather than as a function of days across the entire menstrual cycle (see continuous standardization in the next section of the chapter). When conducting phasic standardization, all menstrual cycle phases are held at fixed lengths, save the length of the luteal phase which will differ based on the participant’s total menstrual cycle length. Each phase length is as follows: menstrual (days 1–5), follicular (days 6–12), ovulatory (days 13–16), luteal (days 17-premenstrual phase), and premenstrual (5 days prior to menstrual bleeding; see Table 1). Each variable of interest is examined as a mean per phase. Each mean per phase variable is calculated by summing each variable per phase and dividing that sum by the total number of days within that menstrual cycle phase.
\nMethod to standardize intensive longitudinal data into the five menstrual cycle phases using phasic standardization.
Data obtained through phasic standardization can be analyzed through the implementation of statistical methods such as repeated-measures ANOVAs or dependent-sample planned contrasts. A repeated-measures ANOVA will identify whether there is a significant difference across menstrual cycle phases on a given dependent variable (e.g., bidding quantity). If the repeated-measures ANOVA reveals a significant effect of MC phase, post-hoc comparisons can be conducted to determine which menstrual cycle phase(s) are characterized by higher/lower levels of the dependent variable relative to which other MC phase(s).
\nSince variability in menstrual cycle length occurs during the luteal phase [15], the luteal phase can be standardized to a seven-day phase, based on the average 28-day cycle, while the remaining phases are held fixed. We refer to this method as continuous standardization. Upon conducting continuous standardization, the length at which each phase is held constant is as follows: 5 days for the menstrual phase (menstrual cycle days 1–5), 7 days for the follicular phase (menstrual cycle days 6–12), 4 days for the ovulatory phase (menstrual cycle days 13–16), and 5 days for the premenstrual phase (5 days prior to menstrual bleeding), accumulating to a total of 21 days. Next, the 21 days are subtracted from the participant’s total menstrual cycle length. The remainder provides the total number of days in the participant’s luteal phase (see Table 2). All participant’s menstrual cycles can then be standardized to a 28-day cycle by allotting 7 standardized days to the participant’s luteal phase length (i.e., 28-day cycle − 21 days (sum of non-luteal phase days) = 7-day luteal phase). Thus, we can express the variance as a ratio of 7/x where x is the participant’s actual luteal phase length (see Table 2). With this luteal phase ratio, we can determine the standardized luteal phase day for each actual luteal phase day. This is calculated by treating the ratio as a factor to be added to day 16 (the last day of the ovulatory phase) to obtain the standardized luteal phase day (see Table 2). Each number obtained is then rounded up (
Method to standardize continuous intensive longitudinal data to a 28-day menstrual cycle.
Menstrual cycle data standardized using continuous standardization can be analyzed using more intricate statistical analyses, such as TVEMs [18]. TVEMs allow for the identification of cyclical changes in addictive behaviors, mood, and their inter-relations as a function of menstrual cycle day by providing an estimate of the relationship between predictor and outcome variables. TVEMs can function similarly to a mediational analysis over time as they identify menstrual cycle days on which elevations (or reductions) in an outcome variable are due to elevations (or reductions) in another variable. For example, in our prior research we used TVEMs to demonstrate that elevations in alcohol consumption during days corresponding to the menstrual phase were explained by elevations in coping drinking motives during these same menstrual cycle days. The implementation of such statistical analyses allows for a more comprehensive understanding of the relationship between addictive behaviors and other factors.
\nIn our prior research [19], we have biologically validated standardizing menstrual cycle length via continuous standardization through the collection of saliva samples. In our research, we collected saliva samples during times of theoretically low (days 1–7) and high (days 18–24) progesterone concentrations [19]. Enzyme-linked immunosorbent assays (ELISA) were then carried out to determine progesterone concentrations for each participant and a paired-sample t-test followed to validate participant’s menstrual cycle day using the identified progesterone concentrations. Results suggested that menstrual cycle days 18–24 (theoretical high) had significantly higher progesterone concentrations than menstrual cycle days 1–7 (theoretical low). Findings provided biological validation for standardizing menstrual cycle data via continuous standardization based on an average 28-day menstrual cycle.
\nTo provide a more comprehensive understanding of the methods employed to standardize data, we have developed two clinically-relevant hypothetical examples. These hypothetical examples were designed to illustrate the types of effects that have been established in the literature on addictive behaviors across the menstrual cycle.
\nIn this hypothetical example, the researchers wanted to examine bidding quantity per menstrual cycle phase to determine if bidding quantity increases or decreases during specific phases of the menstrual cycle relative to other phases of the menstrual cycle (e.g., does bidding frequency increase during the ovulatory phase relative to other menstrual cycle phases?). Let us imagine that this hypothetical data was collected using daily diary methodology. Each day for an entire menstrual cycle, female gambler participants were asked to report their menstrual cycle day and the number of times they bid throughout the day. Here, the researchers collapsed the data by phase, using phasic standardization, to assess whether differences in bidding frequency occurred as a function of menstrual cycle phase.
\nUsing the phasic standardization method, we can produce standardized data that allows for the comparison of data at specific menstrual cycle phases between participants, even though such phases may not be identical in length (see Figure 2 for a hypothetical example). Phasic standardization is conducted in the same manner, regardless of the participant’s menstrual cycle length. Collectively, using phasic standardization allows for the identification of phase-specific differences in addictive behaviors (or mood states, for example) across the menstrual cycle.
\nExample of the mean number of bidding occasions across the five menstrual cycle phases. Error bars represent standard error.
Phasic standardization can be illustrated with a hypothetical example (see Table 3). Here the fictional participant’s 23-day menstrual cycle can be divided into five menstrual cycle phases as outlined in Section 2.1 above. In Table 3, the luteal phase is comprised of all days that are not non-luteal phase days (i.e., days that are not accounted for by another menstrual cycle phase where the other phases are of fixed length). In this hypothetical example, days 17–18 represent the luteal phase. Once the data is divided based on menstrual cycle phase, the bidding quantity variable was averaged for all days within each specific phase. Using phasic standardization, we obtain one datapoint for each variable of interest per phase per participant. Based on the hypothetical case discussed (see Table 3), it appears as though the average number of bidding occasions is lowest during the menstrual phase, peaks during the ovulatory phase, and progressively declines thereafter, consistent with the researcher’s hypothesis. Once collapsed across participants in the sample, these phasic means can be compared using statistics like repeated-measures ANOVA to answer the researcher’s question of whether bidding increases during the ovulatory phase relative to the other menstrual cycle phases.
\nA worked hypothetical example of the phasic method for standardizing a 23-day menstrual cycle across the five phases.
In this second hypothetical example, imagine that a group of researchers wanted to examine cigarette use across the entire menstrual cycle (i.e., across days) to elucidate if, and where, cigarette use increases or decreases across the menstrual cycle. Imagine that these researchers collected information using daily diary surveys to determine participant menstrual cycle day and the number of cigarettes smoked each day across each participant’s entire menstrual cycle. Let us imagine that the researchers in this example were primarily interested in examining cigarette use across the entirety of the menstrual cycle to determine where the level of cigarettes smoked rise and fall (i.e., which menstrual cycle days). This more specific level of detail might not be captured using a phasic evaluation; thus, these researchers would choose to employ continuous standardization rather than phasic standardization.
\nAs mentioned previously, in a normally-cycling sample, we would expect inclusion of individuals who have menstrual cycle lengths that are below and others who have menstrual cycle lengths that are above the average menstrual cycle length of 28 days. Given this, we will provide two examples of continuous standardization using each of these types of cases (i.e., longer than average cycle lengths, shorter than average cycle lengths, respectively) from a hypothetical dataset.
\nUsing this method, we can produce standardized data with all participants having exactly a 28-day standard menstrual cycle (see Figure 3 for an example). This enables us to compare data between participants with variable cycle lengths to determine if specific standardized days are associated with greater (or reduced) addictive behaviors as, following standardization, each day would represent the same time point across participants. Additionally, this process enables us to not only examine specific days, but also identify specific menstrual cycle phases where changes are occurring as all participants have a standardized 28-day cycle with each phase length being consistent across participants. Collectively, we can identify phase-specific and day-specific differences in addictive behaviors across the entirety of the menstrual cycle, using this method of standardization.
\nHypothetical example of the mean number of cigarettes smoked across days of the menstrual cycle. Black lines indicate means and gray lines indicate 95% confidence intervals.
In Section 2.2., we described that the first step in continuous standardization is to calculate the number of luteal phase days by holding all other menstrual cycle phases constant in length. In Figure 4, the number of menstrual cycle days is listed for the average 28-day cycle. This information is then utilized to calculate the number of luteal phase days by subtracting the total number of non-luteal phase days from the participant’s entire menstrual cycle length. For instance, Figure 4 illustrates this by subtracting 21 days (non-luteal phase days) from this hypothetical participant’s entire 25-day menstrual cycle. The remainder (4 days) then becomes the divisor for the number of luteal phase days within the average 28-day cycle (i.e., seven) to identify the factor that must be successively added to day 16. This adding to day 16 occurs four times in this case (the same value as the number of days within the participant’s non-standardized luteal phase) to determine the participant’s new standardized luteal phase days. Following the arrows in Figure 4, we derive four new standardized luteal phase days, which are then rounded to the nearest whole number and incorporated into our dataset.
\nA worked hypothetical example of continuous standardization for a menstrual cycle less than 28-days (i.e., 25-day cycle). Note: A dash (−) signifies a missing data point.
The table in Figure 4 highlights days 17–20 (column one)—the four non-standardized luteal phase days for this hypothetical participant—and the number of cigarettes she smoked on each of these days (column two). Each of the four standardized luteal phase days are then rounded to the nearest whole number (column three). It should be noted that standardizing a cycle with fewer than 28 days to a 28-day cycle will yield a standardized luteal phase with missing data (see resultant standardized dataset in column five of Figure 4). By comparing the red boxes between columns two and five, we can see that the data from the 25-day cycle is carried forward into the ‘standardized data’ column. The resulting data set includes data for this hypothetical participant’s standardized 28-day menstrual cycle. The hypothetical participant’s data (see Figure 4) suggests that cigarette smoking peaks during standardized days 1–5 (i.e., during the menstrual phase) and standardized days 24–28 (i.e., during the premenstrual phase) with a dip mid-cycle (i.e., during the follicular, ovulatory, and luteal phases). To determine where cigarette smoking increases and decreases, the standardized 28-day menstrual cycle can be examined across a larger sample of participants with 28-day standardized cycles using a statistical analysis such as TVEMs.
\nThe process of standardizing a cycle length above 28-days is similar to that employed for cycle lengths less than 28-days (see Figure 5). Using the same hypothetical dataset as an example, we have depicted the standardization method for a second hypothetical participant, this time with a menstrual cycle length of 30 days. When standardizing menstrual cycle data for individuals with cycle lengths greater than 28 days, note that a calculated standardized day may round to the same standardized day as an adjacent day, yielding two data points with identical standardized luteal phase days. In this situation, the data from the identical standardized luteal phase days must be averaged and linked to that standardized luteal phase day. In Figure 5, we see that in column three, two red arrows converge upon standardized luteal phase day 18, for example. Thus, on standardized day 18, the number of cigarettes smoked is averaged from the data for the original days 18 and 19 (i.e., 12 + 14/2 = 13). Then, the new datapoint of 13 is placed into column five to represent standardized data for standardized day 18 for the participant’s standardized 28-day menstrual cycle. A similar process is used for obtaining the cigarettes smoked value for standardized day 21 (see Figure 5). Consistent with the findings for the hypothetical participant in Section 3.2.1., data from this hypothetical participant (see Figure 5) also suggests that cigarette smoking peaks during standardized days 1–5 (i.e., corresponding to the menstrual phase) and standardized days 24–28 (i.e., corresponding to the premenstrual phase) with a dip mid-cycle (i.e., corresponding to the follicular, ovulatory, and luteal phases). Using a larger sample of participants with 28-day standardized cycles, the researchers could employ TVEMs to statistically determine which menstrual cycle days and corresponding phases are associated with increases and decreases in cigarette smoking across a female’s menstrual cycle.
\nA worked hypothetical example of continuous standardization for a menstrual cycle greater than 28-days (i.e., 30-day cycle).
One might similarly standardize data on mood across the menstrual cycle, for example, for these same participants. One could then determine whether elevations in negative mood menstrually and premenstrually, for example, account for rises in cigarette smoking on days corresponding to these same phases, again using TVEMs (e.g., see [19]).
\nTo conclude, this chapter describes two methods to standardize menstrual cycle data, including phasic and continuous standardization. By employing these methods, researchers will be able to more effectively examine fluctuations in addictive behaviors across the menstrual cycle, by allowing data from females with variable cycle lengths to be directly compared or combined across participants. Furthermore, this chapter provides standardization methods which can be used to enhance our understanding of the menstrual cycle as a female-specific factor that may influence important outcome variables in the field of addiction and mental health. Standardized data using continuous standardization also allows for the use of more intricate statistical methods such as TVEM [19] which will significantly benefit behavioral research on the menstrual cycle.
\nAt the time this chapter was written, Ms. Joyce’s graduate studies were supported by a Nova Scotia Graduate Scholarship, a Scotia Scholar Award from the Nova Scotia Health Research Foundation, and a Joseph Armand Bombardier Canada Graduate Scholarship from the Social Sciences and Humanities Research Council of Canada (SSHRC). Dr. Stewart is supported through a Canadian Institutes of Health Research (CIHR) Tier 1 Canada Research Chair in Addictions and Mental Health at Dalhousie University.
\nThe authors have no conflicts of interest to declare.
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People with hearing loss make up a significant 5.3% of the world’s population. The audiogram is an important tool used to determine the degree and type of hearing loss. This chapter presents hearing loss classification, which can aid in clinical diagnosis and help in finding appropriate therapeutic management. Hearing loss is classified based on ear anatomy, type of hearing loss, degree of the disease, and configuration of the audiogram. When the hearing loss is fully characterized, appropriate medical intervention can be assigned.",book:{id:"4654",slug:"update-on-hearing-loss",title:"Update On Hearing Loss",fullTitle:"Update On Hearing Loss"},signatures:"Waleed B. Alshuaib, Jasem M. Al-Kandari and Sonia M. 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The few clinical studies have shown that abstention from caffeine has little effect in patients with Meniere’s disease, both in relation to vertigo, tinnitus and hearing loss.",book:{id:"5454",slug:"up-to-date-on-meniere-s-disease",title:"Up to Date on Meniere's Disease",fullTitle:"Up to Date on Meniere's Disease"},signatures:"Alleluia Lima Losno Ledesma, Monique Antunes de Souza\nChelminski Barreto and Carlos Augusto Costa Pires de Oliveira",authors:[{id:"68849",title:"Prof.",name:"Carlos Augusto C. P.",middleName:null,surname:"Oliveira",slug:"carlos-augusto-c.-p.-oliveira",fullName:"Carlos Augusto C. P. Oliveira"},{id:"175482",title:"Dr.",name:"Monique",middleName:null,surname:"Barreto",slug:"monique-barreto",fullName:"Monique Barreto"},{id:"194400",title:"Dr.",name:"Alleluia",middleName:"Lima",surname:"Losno Ledesma",slug:"alleluia-losno-ledesma",fullName:"Alleluia Losno Ledesma"}]},{id:"53121",title:"Audiological Assessment in Meniere’s Disease",slug:"audiological-assessment-in-meniere-s-disease",totalDownloads:2568,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Meniere’s disease is a progressive disorder characterized by recurrent episodes of spontaneous vertigo, sensorineural hearing loss and tinnitus, often with a feeling of fullness in the ear. The exact ethology is not known. In 1972, a diagnostic criterion for Meniere’s disease was proposed by American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS), and till date, it has been revised twice in the years 1985 and 1995. The principal audiological investigation is pure tone audiometry combined with a glycerol test. Speech audiometry and otoacoustic emissions also play a limited role. The value of electrocochleography is limited.",book:{id:"5454",slug:"up-to-date-on-meniere-s-disease",title:"Up to Date on Meniere's Disease",fullTitle:"Up to Date on Meniere's Disease"},signatures:"Dinesh Kumar Sharma",authors:[{id:"189074",title:"Dr.",name:"Dinesh",middleName:null,surname:"Sharma",slug:"dinesh-sharma",fullName:"Dinesh Sharma"}]},{id:"49108",title:"Hearing Loss and the Voice",slug:"hearing-loss-and-the-voice",totalDownloads:3300,totalCrossrefCites:2,totalDimensionsCites:10,abstract:"The voice varies according to the context of speech and to the physical and psychological conditions of the human being, and there is always a normal standard for the vocal output. Hearing loss can impair voce production, causing social, educational, and speech limitations, with specific deviation of the communication related to speech and voice. Usually, the voice is not the main focus of the speech-language pathology therapy with individuals with hearing loss, but its deviations can represent such a negative impact on this population that it can interfere on speech intelligibility and crucially compromise the social integration of the individual. The literature vastly explores acoustic and perceptual characteristics of children and adults with hearing loss. Voice problems in individuals with this impairment are directly related to its type and severity, age, gender, and type of hearing device used. While individuals with mild and moderate hearing loss can only present problems with resonance, severely impaired individuals may lack intensity and frequency control, among other alterations. The commonly found vocal deviations include strain, breathiness, roughness, monotone, absence of rhythm, unpleasant quality, hoarseness, vocal fatigue, high pitch, reduced volume, loudness with excessive variation, unbalanced resonance, altered breathing pattern, brusque vocal attack, and imprecise articulation. These characteristics are justified by the incapability of the deaf to control their vocal performance due to the lack of auditory monitoring of their own voice, caused by the hearing loss. Hence, the development of an intelligible speech with a good quality of voice on the hearing impaired is a challenge, despite the sophisticated technological advances of hearing aids, cochlear implants and other implantable devices. The purpose of this chapter is therefore to present an extensive review of the literature and describe our experience regarding the evaluation, diagnosis, and treatment of voice disorders in individuals with hearing loss.",book:{id:"4654",slug:"update-on-hearing-loss",title:"Update On Hearing Loss",fullTitle:"Update On Hearing Loss"},signatures:"Ana Cristina Coelho, Daniela Malta Medved and Alcione Ghedini\nBrasolotto",authors:[{id:"174260",title:"M.Sc.",name:"Ana Cristina",middleName:null,surname:"Coelho",slug:"ana-cristina-coelho",fullName:"Ana Cristina Coelho"},{id:"174643",title:"Dr.",name:"Alcione",middleName:null,surname:"Brasolotto",slug:"alcione-brasolotto",fullName:"Alcione Brasolotto"},{id:"174644",title:"MSc.",name:"Daniela",middleName:null,surname:"Medved",slug:"daniela-medved",fullName:"Daniela Medved"}]},{id:"53473",title:"Hearing and Vestibular Testing in Menière’s Disease",slug:"hearing-and-vestibular-testing-in-meni-re-s-disease",totalDownloads:1851,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Audiological and vestibular testing plays an important role in diagnosis of Menière’s disease,as disease per se and as staging diagnosis. A battery of tests are recommended in order to have a better evaluation of the disease. Audiological testing includes pure tone audiometry, with highlights of bone conduction especially in acute episodes of Menière’s disease, speech audiometry and glycerol test when hearing loss is documented, ABR and electrocochleography. Besides these investigations, vestibular investigations are also recommended in order to evaluate the degree of vestibular lesion present from the beginning of Menière’s disease—electro- and videonystagmography, head impulse test, vestibular evoked myogenic potentials and computerized dynamic posturography.",book:{id:"5454",slug:"up-to-date-on-meniere-s-disease",title:"Up to Date on Meniere's Disease",fullTitle:"Up to Date on Meniere's Disease"},signatures:"Madalina Gabriela Georgescu",authors:[{id:"189076",title:"Associate Prof.",name:"Madalina",middleName:null,surname:"Georgescu",slug:"madalina-georgescu",fullName:"Madalina Georgescu"}]}],onlineFirstChaptersFilter:{topicId:"1099",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:290,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:12,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:17,paginationItems:[{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:12,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:2,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81557",title:"Object Tracking Using Adapted Optical Flow",doi:"10.5772/intechopen.102863",signatures:"Ronaldo Ferreira, Joaquim José de Castro Ferreira and António José Ribeiro Neves",slug:"object-tracking-using-adapted-optical-flow",totalDownloads:11,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Information Extraction and Object Tracking in Digital Video",coverURL:"https://cdn.intechopen.com/books/images_new/10652.jpg",subseries:{id:"24",title:"Computer Vision"}}},{id:"81558",title:"Thresholding Image Techniques for Plant Segmentation",doi:"10.5772/intechopen.104587",signatures:"Miguel Ángel Castillo-Martínez, Francisco Javier Gallegos-Funes, Blanca E. Carvajal-Gámez, Guillermo Urriolagoitia-Sosa and Alberto J. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:249,paginationItems:[{id:"274452",title:"Dr.",name:"Yousif",middleName:"Mohamed",surname:"Abdallah",slug:"yousif-abdallah",fullName:"Yousif Abdallah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274452/images/8324_n.jpg",biography:"I certainly enjoyed my experience in Radiotherapy and Nuclear Medicine, particularly it has been in different institutions and hospitals with different Medical Cultures and allocated resources. Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"93",type:"subseries",title:"Inclusivity and Social Equity",keywords:"Social contract, SDG, Human rights, Inclusiveness, Equity, Democracy, Personal learning, Collaboration, Glocalization",scope:"\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems.
\r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",annualVolume:11966,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},{id:"39",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
",annualVolume:11967,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null,editorialBoard:[{id:"177015",title:"Prof.",name:"Elke Jurandy",middleName:null,surname:"Bran Nogueira Cardoso",fullName:"Elke Jurandy Bran Nogueira Cardoso",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGxzQAG/Profile_Picture_2022-03-25T08:32:33.jpg",institutionString:"Universidade de São Paulo, Brazil",institution:null},{id:"211260",title:"Dr.",name:"Sandra",middleName:null,surname:"Ricart",fullName:"Sandra Ricart",profilePictureURL:"https://mts.intechopen.com/storage/users/211260/images/system/211260.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}}]},{id:"40",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"